INTRODUCTION The coronavirus disease 2019 (COVID-19) first reported in Wuhan China in December 2019 is a global pandemic that is threatening the health and wellbeing of people worldwide. To date there have been more than 274 million reported cases and 5.3 million deaths. The Omicron variant first documented in the City of Tshwane, Gauteng Province, South Africa on 9 November 2021 led to exponential increases in cases and a sharp rise in hospital admissions. The clinical profile of patients admitted at a large hospital in Tshwane is compared with previous waves. METHODS The methods should describe what study design you employed for the study and what your sample size was, as it is this is mainly results. 466 hospital COVID-19 admissions since 14 November 2021 were compared to 3976 prior admissions since 4 May 2020. Ninety-eight patient records at peak bed occupancy during the outbreak were reviewed for primary indication for admission, clinical severity, oxygen supplementation level, vaccination and prior COVID-19 infection. Provincial and city-wide daily cases and reported deaths hospitalizations and excess deaths data were sourced from the NICD, the National Department of Health and the South African Medical Research Council. RESULTS Deaths and ICU admissions were 4.5% vs 21.3% (p<0.00001), and 1% vs 4.3% (p<0.00001); length of stay was 4.0 days vs 8.8 days; and mean age was 39 years vs 49 years for the Omicron and previous waves respectively. Admissions peaked and declined rapidly with peak bed occupancy at 51% of highest previous peak. Sixty two (63%) patients in COVID-19 wards had incidental COVID-19 following a positive SARS-CoV-2 PCR test . Only one third (36) had COVID-19 pneumonia, of which 72% had mild to moderate disease. The remaining 38% required high care or ICU admission. Fewer than half (45%) of patients in COVID-19 wards compared to 99.5% in the first wave required oxygen supplementation. City and provincial rates show decoupling of cases, hospitalisations and deaths compared to previous waves, corroborating the clinical findings of milder omicron disease in the hospital. CONCLUSION There was decreased severity of disease in the Omicron driven fourth wave in the City of Tshwane, its first global epicentre.

Background The interaction between COVID-19, non-communicable diseases, and chronic infectious diseases such as HIV and tuberculosis is unclear, particularly in low-income and middle-income countries in Africa. South Africa has a national HIV prevalence of 19% among people aged 15-49 years and a tuberculosis prevalence of 0•7% in people of all ages. Using a nationally representative hospital surveillance system in South Africa, we aimed to investigate the factors associated with in-hospital mortality among patients with COVID-19. MethodsIn this cohort study, we used data submitted to DATCOV, a national active hospital surveillance system for COVID-19 hospital admissions, for patients admitted to hospital with laboratory-confirmed SARS-CoV-2 infection between March 5, 2020, and March 27, 2021. Age, sex, race or ethnicity, and comorbidities (hypertension, diabetes, chronic cardiac disease, chronic pulmonary disease and asthma, chronic renal disease, malignancy in the past 5 years, HIV, and past and current tuberculosis) were considered as risk factors for COVID-19-related in-hospital mortality. COVID-19 in-hospital mortality, the main outcome, was defined as a death related to COVID-19 that occurred during the hospital stay and excluded deaths that occurred because of other causes or after discharge from hospital; therefore, only patients with a known in-hospital outcome (died or discharged alive) were included. Chained equation multiple imputation was used to account for missing data and random-effects multivariable logistic regression models were used to assess the role of HIV status and underlying comorbidities on COVID-19 in-hospital mortality. FindingsAmong the 219 265 individuals admitted to hospital with laboratory-confirmed SARS-CoV-2 infection and known in-hospital outcome data, 51 037 (23•3%) died. Most commonly observed comorbidities among individuals with available data were hypertension in 61 098 (37•4%) of 163 350, diabetes in 43 885 (27•4%) of 159 932, and HIV in 13 793 (9•1%) of 151 779. Tuberculosis was reported in 5282 (3•6%) of 146 381 individuals. Increasing age was the strongest predictor of COVID-19 in-hospital mortality. Other factors associated were HIV infection (adjusted odds ratio 1•34, 95% CI 1•27-1•43), past tuberculosis (1•26, 1•15-1•38), current tuberculosis (1•42, 1•22-1•64), and both past and current tuberculosis (1•48, 1•32-1•67) compared with never tuberculosis, as well as other described risk factors for COVID-19, such as male sex; non-White race; underlying hypertension, diabetes, chronic cardiac disease, chronic renal disease, and malignancy in the past 5 years; and treatment in the public health sector. After adjusting for other factors, people with HIV not on antiretroviral therapy (ART; adjusted odds ratio 1•45, 95% CI 1•22-1•72) were more likely to die in hospital than were people with HIV on ART. Among people with HIV, the prevalence of other comorbidities was 29•2% compared with 30•8% among HIV-uninfected individuals. Increasing number of comorbidities was associated with...

Background The first wave of COVID-19 in South Africa peaked in July, 2020, and a larger second wave peaked in January, 2021, in which the SARS-CoV-2 501Y.V2 (Beta) lineage predominated. We aimed to compare in-hospital mortality and other patient characteristics between the first and second waves.Methods In this prospective cohort study, we analysed data from the DATCOV national active surveillance system for COVID-19 admissions to hospital from March 5, 2020, to March 27, 2021. The system contained data from all hospitals in South Africa that have admitted a patient with COVID-19. We used incidence risk for admission to hospital and determined cutoff dates to define five wave periods: pre-wave 1, wave 1, post-wave 1, wave 2, and post-wave 2. We compared the characteristics of patients with COVID-19 who were admitted to hospital in wave 1 and wave 2, and risk factors for in-hospital mortality accounting for wave period using random-effect multivariable logistic regression.Findings Peak rates of COVID-19 cases, admissions, and in-hospital deaths in the second wave exceeded rates in the first wave: COVID-19 cases, 240•4 cases per 100 000 people vs 136•0 cases per 100 000 people; admissions, 27•9 admissions per 100 000 people vs 16•1 admissions per 100 000 people; deaths, 8•3 deaths per 100 000 people vs 3•6 deaths per 100 000 people. The weekly average growth rate in hospital admissions was 20% in wave 1 and 43% in wave 2 (ratio of growth rate in wave 2 compared with wave 1 was 1•19, 95% CI 1•18-1•20). Compared with the first wave, individuals admitted to hospital in the second wave were more likely to be age 40-64 years (adjusted odds ratio [aOR] 1•22, 95% CI 1•14-1•31), and older than 65 years (aOR 1•38, 1•25-1•52), compared with younger than 40 years; of Mixed race (aOR 1•21, 1•06-1•38) compared with White race; and admitted in the public sector (aOR 1•65, 1•41-1•92); and less likely to be Black (aOR 0•53, 0•47-0•60) and Indian (aOR 0•77, 0•66-0•91), compared with White; and have a comorbid condition (aOR 0•60, 0•55-0•67).For multivariable analysis, after adjusting for weekly COVID-19 hospital admissions, there was a 31% increased risk of in-hospital mortality in the second wave (aOR 1•31, 95% CI 1•28-1•35). In-hospital case-fatality risk increased from 17•7% in weeks of low admission (<3500 admissions) to 26•9% in weeks of very high admission (>8000 admissions; aOR 1•24, 1•17-1•32).Interpretation In South Africa, the second wave was associated with higher incidence of COVID-19, more rapid increase in admissions to hospital, and increased in-hospital mortality. Although some of the increased mortality can be explained by admissions in the second wave being more likely in older individuals, in the public sector, and by the increased health system pressure, a residual increase in mortality of patients admitted to hospital could be related to the new Beta lineage.

Individuals with HIV co-infected with PTB have a higher proportion of infiltrates and a lower proportion of cavitations relative to the HIV-uninfected PTB individuals. The absence of classical upper lobe cavitatory disease on CXR does not exclude PTB in individuals with HIV.

Introduction Informal waste recyclers contribute significantly to waste removal in South Africa. Waste recyclers face health hazards which are associated with handling and disposal of waste, a lack of personal protective wear and inaccessibility to occupational health care services. Consequently, accessing health care within the public health care sector is important for health outcomes in this population. This study assesses health care access of informal waste recyclers in South Africa to establish baseline information for health planning for potential inclusion of informal waste recyclers into occupational health services. Methods A cross-sectional study of informal waste recyclers in two landfill sites in Johannesburg was conducted from March 2018. A standardized structured questionnaire was used to collect information on sociodemographic details, health care utilization, barriers to access and acceptability and affordability of health care. Factors associated with health care utilization were assessed using logistic regression. Results A total of 363 informal waste recyclers were included in the study. Less than half of informal waste recyclers (41.0%) used health care facilities in the last 12 months. Those who accessed services chose to use facilities close to where they live (87.0%). Barriers to accessing health care services included long waiting periods (36.6%), being unable to take time off work (26.3%) and transport problems (13%). In the univariate analysis, factors such as gender and being treated well at the clinic and location of the health care facility were associated with health care utilization (OR: 1.

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